Glacier change in China over past decades: Spatiotemporal patterns and influencing factors

Su, Bo; Xiao, Cunde; Chen, Deliang; Huang, Yi; Che, Yue; Zhao, Hongyu; Zou, Mingbo; Guo, Rong; Wang, Xuejia; Li, Xin; Guo, Wei; Liu, Shiyin; Yao, Tandong

doi:10.1016/j.earscirev.2022.103926

Cited by 45 publications

(30 citation statements)

References 106 publications

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“…1 showing a decrease of −0.0142 m w.e. yr −1 ( Su et al, 2022 ). All these values were statistically significant ( p < 0.0001).…”

Section: Resultsmentioning

confidence: 99%

“…This has implications for sediment yield and geohazards, as well as water supply ( Knight & Harrison, 2013 ; Mukherji et al, 2015 ; Milner et al, 2017 ) and water management strategies ( López-Moreno, Beniston & García-Ruiz, 2008 ; Bombelli et al, 2019 ). Contemporary snow and glacier retreat in mountains is already impacting on the development and sustainability of mountain tourism and conservation of the natural environment ( Purdie, 2013 ; Pröbstl-Haider, Dabrowska & Haider, 2016 ; Su et al, 2022 ) and its built heritage ( Duvillard et al, 2019 ).…”

Section: Resultsmentioning

confidence: 99%

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Scientists’ warning of the impacts of climate change on mountains

Knight¹

2022

PeerJ

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Mountains are highly diverse in areal extent, geological and climatic context, ecosystems and human activity. As such, mountain environments worldwide are particularly sensitive to the effects of anthropogenic climate change (global warming) as a result of their unique heat balance properties and the presence of climatically-sensitive snow, ice, permafrost and ecosystems. Consequently, mountain systems—in particular cryospheric ones—are currently undergoing unprecedented changes in the Anthropocene. This study identifies and discusses four of the major properties of mountains upon which anthropogenic climate change can impact, and indeed is already doing so. These properties are: the changing mountain cryosphere of glaciers and permafrost; mountain hazards and risk; mountain ecosystems and their services; and mountain communities and infrastructure. It is notable that changes in these different mountain properties do not follow a predictable trajectory of evolution in response to anthropogenic climate change. This demonstrates that different elements of mountain systems exhibit different sensitivities to forcing. The interconnections between these different properties highlight that mountains should be considered as integrated biophysical systems, of which human activity is part. Interrelationships between these mountain properties are discussed through a model of mountain socio-biophysical systems, which provides a framework for examining climate impacts and vulnerabilities. Managing the risks associated with ongoing climate change in mountains requires an integrated approach to climate change impacts monitoring and management.

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“…1 showing a decrease of −0.0142 m w.e. yr −1 ( Su et al, 2022 ). All these values were statistically significant ( p < 0.0001).…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Scientists’ warning of the impacts of climate change on mountains

Knight¹

2022

PeerJ

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“…laciers are sensitive to climate change, and the widespread shrinking of glaciers globally has been caused by climate warming in recent years [1][2][3]. The Qinghai-Tibet Plateau (QTP) is known as the Third Pole of the Earth and the Water Tower of Asia, because its unique geographical conditions and abundant water sources [4], [5]. The QTP has also developed the largest mountain glaciers among the middle-and low-latitude regions in the world [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Glacier Retreating Analysis on the Southeastern Tibetan Plateau via Multisource Remote Sensing Data

Xiao

Cai

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Accurate multitemporal glacier change investigations and analyses are lacking on the southeastern Tibetan Plateau (SETP). A combination of photogrammetry, optical remote sensing and synthetic aperture radar (SAR) datasets can accurately identify large-scale glaciers; In the present study, glaciers in three periods on the SETP (1970s, 2000, 2020) were identified from multisource remote sensing data based on a deep learning method and manual visual interpretation, and multitemporal glacial inventory data from relatively highfrequency source imagery. Totals of 11648, 12993, and 11875 glaciers were identified in the 1970s, 2000, and 2020, with total areas of 13372.08 km 2 , 11692.31 km 2 , and 10612.94 km 2 , respectively.The general distribution of SETP glaciers was identified to be typical of alpine glaciers dominated by small-sized glaciers. The average elevation of glaciers was approximately 5000 m; the slopes were mostly lower than 40°, and the main aspect was southeast, followed by south and southwest. The glaciers retreated from the 1970s to 2020, and a total glacier area of approximately 2759.14 km 2 was degraded during this time, with an average annual melting rate of 0.45% yr -1 . Rising summer temperatures may be the driving force behind the continuous decline in the glacier area. Overall, the results obtained in this study showed relatively low uncertainty involved in the identification of glaciers compared to some previous studies. The results can provide accurate glacier information for glacier monitoring and modeling studies on the SETP.

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“…Moreover, large amounts of snow cover can also lead to snow disasters, resulting in extensive damage to human life and property (Ma et al ., 2021). With global warming, snow cover and its properties have changed with significant spatial heterogeneity (Su et al ., 2019; Pulliainen et al ., 2020), with dramatic impacts on regional climates, water supplies and socioeconomic activities (Biemans et al ., 2019; Kraaijenbrink et al ., 2021; Su et al ., 2022a).…”

Section: Introductionmentioning

confidence: 99%

Snow depth variability across the Qinghai Plateau and its influencing factors during 1980–2018

Zhang

Mao

et al. 2022

Intl Journal of Climatology

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As a crucial component of the climate system, snow cover plays an important role on surface energy budgets, hydrological cycles and socioeconomic development. This paper investigated the spatiotemporal patterns of snow depth across the Qinghai Plateau (QP) during 1980–2018 based on passive microwave (PMW) satellite observation and reanalysis products. The study identified the relationships between the changes in PMW snow depth and topographic features and revealed the impact of climatic variables (air temperature, precipitation and wind speed) and large‐scale atmospheric circulations on observed snow depth variability. The results show that the spatial pattern of snow depth climatology is similar in all datasets, except in terms of magnitude, with high values in the southern and southeastern parts of the QP and low values in the eastern and northwestern parts. Average snow depth correlates positively with precipitation, elevation and slope, and negatively with air temperature and wind speed. The long‐term trends in snow depth vary with the season and the datasets. The PMW snow depth across the QP shows a significant annual (−0.125 cm·decades−1, p < .10) and spring (−0.184 cm·decades−1, p < .05) negative trend, while snow depth for ERA5 and MERRA2 does not present significant trends. Air temperature dominates total snow depth variation over the QP, explaining 43.85, 24.88 and 47.28% of annual, winter and spring PMW snow depth variations, which significantly affects snow depth variations in most parts of the QP, yet the effects of precipitation and wind speed on snow depth variation exhibit significant regional differences, and atmospheric circulations (e.g., AMO) also have a remarkable controlling effect on some localized areas.

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Glacier change in China over past decades: Spatiotemporal patterns and influencing factors

Cited by 45 publications

References 106 publications

Scientists’ warning of the impacts of climate change on mountains

Scientists’ warning of the impacts of climate change on mountains

Glacier Retreating Analysis on the Southeastern Tibetan Plateau via Multisource Remote Sensing Data

Snow depth variability across the Qinghai Plateau and its influencing factors during 1980–2018

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